Descriptor Of Catalytic Activity Research Articles

Oxidation of 5-Hydroxymethylfurfural into 2,5-Diformylfuran on Alkali Doped Ru/C Catalysts. Electron Properties of Ruthenium Species as Descriptor of Catalytic Activity.

Selective aerobic oxidation of 5-hydroxymethylfurfural into 2,5-diformylfuran has been achieved on alkali doped Ru/C catalyst. Optimization of Ru metal nanoparticles, as well as the nature and amount of the alkali dopant have been performed. The results showed that doping the Ru/C catalyst with controlled amount of potassium increases the catalytic activity, 2.5 fold with respect to the non-doped sample. Spectroscopic studies showed that these differences in activity can be attributed to a different oxidation reaction mechanism associated to the presence of electron rich Ru species in the promoted sample that facilitate the dissociation of O2, while prevents the oxidation of the metal. The Ru/C-K doped catalyst resulted very stable against leaching and metal sintering, being possible the reuse over several consecutive runs. Moreover, the catalyst could be successfully applied to the oxidation of different alcohols.

Nondissociative activation of O2 for SO2 oxidation on metal-free N-doped carbocatalyst

Oxygen molecules (O2) are generally one of the most important and economic oxidants for a large range of chemical processes. Due to its intrinsically sluggish nature, exploring a suitable catalyst for activation has long been a challenging issue. Based on DFT calculations, we proposed a new mechanism for O2 activation, where O2 could be activated to form an adsorbed peroxide species on a metal-free carbocatalyst, rather than be dissociated to form two adsorbed O atoms as conventional. This kind of activation results in a SO2-O2 coadsorbed intermediate, which separates a high-barrier reaction into two concerted low-barrier (∼ 0.3 eV) reactions. The number of active electrons of the active C sites was proposed to be a descriptor of catalytic activity. Our results indicate a nondissociative mechanism for O2 activation on a metal-free carbocatalyst and provide new insight into SO2 catalytic oxidation at low temperature.

Can the local electric field be a descriptor of catalytic activity? A case study on chorismate mutase.

The current theoretical perception of enzymatic activity is highly reliant on the determination of the activation energy of the reactions, which is often calculated using computationally demanding quantum mechanical calculations. With the ever-increasing use of bioengineering techniques that produce too many variants of the same enzyme, a fast and accurate way to study the relative efficiency of enzymes is currently in high demand. Here, we propose the local electric field (LEF) of the enzyme along the reaction axis as a descriptor for the enzymatic activity using the example of chorismate mutase in its native form and several variants (R90A, R90G, and R90K/C88S). The study shows a direct correlation between the calculated enzymatic EF and the enzymatic activity for all the complexes. MD simulations of the Michaelis complex and the transition state analog (TSA) show a stabilizing force on the TSA due to the enzymatic EF. QM/MM and QM-only DFT calculations in the presence of an external electric field (EEF) oriented along the reaction axis show that the electric field can interact with the dipole moment of the TS, thereby stabilizing it and thus lowering the activation energy.

Designing C3N-supported single atom catalysts for efficient nitrogen reduction based on descriptor of catalytic activity

The two-step strategy screening based high throughput calculation is an effective method to search for highly active single atom catalysts (SACs) for efficient nitrogen reduction reaction (NRR), sharing a common feature of active metal centers MN4. However, this method faces the lack of descriptor for designing SACs due to limited data. Herein we proposed a robust empirical rule to estimate 312 credible limiting potentials for NRR over 104 C3N-supported SACs. It is found that the limiting potential scales clearly with the adsorption free energies of two key reaction intermediates (∗N2H and ∗NH2), which are significantly dependent on the structure relating descriptor φ, and the activity of SACs with and without N coordination exhibits similar catalytic efficiency. We identified four high-performance SACs having moieties of CrC2N2, CrC4, MnC4 and OsC4 with high selectivity towards NRR and competitive limiting potentials of −0.40, −0.45, −0.53 and −0.54 V, respectively. The φ values for these four SACs are around 19–25 which fall within its optimal ranges of 20–25 validating its prediction fidelity. This work broadens the discovery of two-dimensional carbon-nitrides supported SACs free of N coordination towards efficient N2 reduction and opens a new route of descriptor-guided design of efficient SACs for electrocatalysis process.

Machine-learning-accelerated discovery of single-atom catalysts based on bidirectional activation mechanism

Single-atom catalysts (SACs) have provided new impetus to the field of catalysis because of their high activity, high selectivity, and theoretically full utilization of active atoms. However, the ambiguous activation mechanism prevents a clear understanding of the structure-activity relationship and results in a great challenge of rational design of SACs. Herein, by combining density functional theory (DFT) calculations with machine learning (ML), we explore 126 SACs to analyze and develop the structure-activity relationship for the electrocatalytic nitrogen reduction reaction (NRR). We first propose a bidirectional activation mechanism with a new descriptor for catalytic activity, which provides new insights for the rational design of SACs. More importantly, we establish a ML model for predicting the catalytic performance of NRR, validated by both DFT calculations and experimental works. The successful ML prediction in this work helps with the accelerated design and discovery of new catalysts by computational screening with high practical significance. • A bidirectional activation mechanism is proposed for building catalytic theory • A new descriptor of N ie-d is applied for evalulating the catalytic activity for NRR • The developed ML model could predict the catalytic performance of SACs accurately Single-atom catalysts (SACs) have provided a new impetus to the field of catalysis. The key challenges in the development of SACs are to explore the structure-activity relationship and predict the catalytic performance of SACs. Our work addresses these challenges by examining a series of SACs supported on 2D materials via the combination of density functional theory (DFT) calculations and machine learning (ML). The proposed “bidirectional activation mechanism” not only explains some experimental results but also can be extended to other catalytic reactions, laying the foundations for constructing catalytic theory. Moreover, the developed ML model could predict the catalytic activity of SACs for the nitrogen reduction reaction with reliable accuracy, as validated by previous DFT and experimental work. This work provides new insights into catalysis theory and will accelerate the discovery of SACs, hugely influencing the real-world energy field. Singh and co-workers propose a bidirectional activation mechanism with a new descriptor of N ie-d for providing insights into catalysis on the basis of DFT calculations. Their developed ML model with high accuracy could accelerate the design of SACs for NRR.

Computational catalysis for metal-organic frameworks: An overview

Metal-organic frameworks (MOFs), a family of porous hybrid organic/inorganic materials, have shown great promise for many challenging chemical applications including gas separations, catalysis, and sensors. Numerous recent articles explore the field of catalytically active MOFs at an experimental and computational level. The stability, porosity, and periodic nature of MOFs allow them to act as both the active catalyst as well as supporting material to single atoms or small metal clusters. This review highlights recent work performed on catalytic reactions promoted by MOFs from a computational and theoretical standpoint. Computational modeling includes the elucidation of reaction mechanisms, the characterization of electronic structure effects of key intermediates and transition states, and the interpretation of experimental data. These topics are covered in this review article, and examples from the recent literature are presented. Studies that aim to better understand structure–function relations such as descriptors of catalytic activity have the potential to contribute to the design of new MOF catalysts are also included. We believe that the future of computational MOF catalysis will involve the use of high-throughput virtual screening and machine learning methods, some aspects of which are discussed in the current review.

Efficient bi-directional OER/ORR catalysis of metal-free C6H4NO2/g-C3N4: Density functional theory approaches

Metal-free catalyst with favorable advantages of nonpolluting, cost-effective and stable catalytic performances may be used in various redox reactions. In this paper, we design a series of C6H4NO2/g-C3N4 composites by combining a polar nitrobenzene molecule with g-C3N4 monolayer using density functional theory calculations. The electrocatalytic performances during oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) are substantially improved thanks to the electron redistributions of g-C3N4 substrate. One composite specimen exhibits the lowest bi-directional OER/ORR overpotentials of 0.14/0.14 V, and the most stable composite specimen has OER/ORR overpotentials of 0.27/0.39 V. The number of active electrons in active atom, as descriptor of catalytic activity, can accurately estimate the OER and ORR activity of metal-free electrocatalysts. The modification strategy would be extended to design high-efficiency metal-free electrocatalysts.

Experimentally Measurable Surface <i>d</i> Charge as a Descriptor for Catalytic Activity

Experimentally Measurable Surface <i>d</i> Charge as a Descriptor for Catalytic Activity

Influence of the Fe:Ni Ratio and Reaction Temperature on the Efficiency of (FexNi1–x)9S8 Electrocatalysts Applied in the Hydrogen Evolution Reaction

Inspired by our recent finding that Fe4.5Ni4.5S8 rock is a highly active electrocatalyst for HER, we set out to explore the influence of the Fe:Ni ratio on the performance of the catalyst. We herein describe the synthesis of (FexNi1–x)9S8 (x = 0–1) along with a detailed elemental composition analysis. Furthermore, using linear sweep voltammetry, we show that the increase in the iron or nickel content, respectively, lowers the activity of the electrocatalyst toward HER. Electrochemical surface area analysis (ECSA) clearly indicates the highest amount of active sites for a Fe:Ni ratio of 1:1 on the electrode surface pointing at an altered surface composition of iron and nickel for the other materials. Specific metal–metal interactions seem to be of key importance for the high electrocatalytic HER activity, which is supported by DFT calculations of several surface structures using the surface energy as a descriptor of catalytic activity. In addition, we show that a temperature increase leads to a significant decrease of the overpotential and gain in HER activity. Thus, we showcase the necessity to investigate the material structure, composition and reaction conditions when evaluating electrocatalysts.

Tuning core-shell interactions in tungsten carbide-Pt nanoparticles for the hydrogen evolution reaction.

Platinum (Pt) is among the best electrocatalysts for the hydrogen evolution reaction (HER), a potentially fossil-free route for hydrogen production. Reduction in Pt loading and overall catalyst cost, without sacrificing catalytic activity, can be achieved by the synthesis of stable core-shell nanoparticles of transition-metal carbides and Pt. We employ density-functional theory (DFT) calculations to study and contrast the suitability of the α and β phases of tungsten carbide (WC) as support (core) materials for Pt shells. We examine the thermodynamic stability of 1-2 layers of Pt on α- and β-WC surfaces, carefully accounting for the delicate balance between epitaxial mismatch strains and chemical bonding between cores and shells. We also study the effects of alloying β-WC with Ti to modulate the stability and electronic structure of the core-shell structures. We compare the electronic structures of Pt overlayers supported on α-WC and β-TixW1-xC surfaces and compare their activities for HER using the hydrogen binding energy as a descriptor of catalytic activity. Our studies reveal that moderate Ti doping of the metastable β-WC phase significantly improves its stability and, with merely two layers of Pt loading, HER activity comparable or superior to Pt(111) can be attained. Overall, our results provide detailed insight into experimental observations of the excellent stability and high catalytic activity of β-TixW1-xC@Pt core-shell nanoparticles.

First-principles investigation of Pd3Bi as a catalyst for the oxygen reduction reaction

A slab model was used to examine the geometric and electronic structure of Pd3Bi based on first principles density functional theory (DFT) calculations. The structural and electronic properties were determined for bulk and slab models. Atomic oxygen was adsorbed on all adsorption sites of (100) Pd3Bi. The adsorption energy and the d-band center were used as descriptors of catalytic activity and were compared to those of Pt and Pd. The descriptors suggest that Pd3Bi would have a better catalytic activity towards the ORR than pure Pd.

Surface Energy as a Descriptor of Catalytic Activity

Computational searches for catalysts of the hydrogen evolution reaction commonly use the hydrogen binding energy (HBE) as a predictor of catalytic activity. Accurate evaluation of the HBE, however, can involve large periodic supercell slab models that render high-throughput screening relatively expensive. In contrast, calculations of other relevant surface properties, such as the surface energy, work function, and potential of zero charge (PZC), require only small surface unit cells and are hence less expensive to compute. Correlations between catalytic activity and these surface properties warrant exploration because of this reduced computational cost. Here, we use density functional theory in conjunction with three different exchange-correlation functionals—the local density approximation (LDA), the Perdew–Burke–Ernzerhof (PBE) generalized gradient approximation, and the PBEsol functional (a reparameterization of the PBE functional)—to calculate the lattice constants, surface energy, cohesive energy, an...

Molecular bonding-based descriptors for surface adsorption and reactivity

Descriptors, quantities that correlate with catalytically interesting quantities, are widely used in computational catalyst screenings. For example, adsorption energies of atomic species (O, C, etc.) are often employed as descriptors of catalytic activity, in conjunction with appropriate scaling and Brønsted–Evans–Polanyi relations. While very successful in terms of their predictive value, the reaction-specific mechanistic insight gained from such relations can be limited since adsorption energy descriptors often correlate indirectly with catalytic activity. To this end, we have developed a novel class of descriptors based on molecular bonding, characterizing the intramolecular bonding of adsorbed reactants in terms of two-center bonding derived on the basis of Natural Bond Orbital analysis. We demonstrate this approach by examining a diverse set of reactions across a variety of transition metal surfaces. We find that these bonding-based descriptors have a direct connection with the surface–adsorbate interactions that mediate catalysis, explicitly treating the bond breakage/formation that accompanies the rearrangement of atomic contacts. In many cases, we can interpret these interactions in terms of adsorbate “pre-activation”, reflecting the intrinsic locality of surface reactions. We anticipate that this molecular bonding-based approach can help elucidate more comprehensive mechanistic insight into surface-catalyzed reactions and facilitate the unification of concepts from homogeneous and heterogeneous catalysis.

Band-gap energy as a descriptor of catalytic activity for propene oxidation over mixed metal oxide catalysts.

The development of a descriptor or descriptors that can relate the activity of catalysts to their physical properties is a major objective of catalysis research. In this study, we have found that the apparent activation energy for propene oxidation to acrolein over scheelite-structured, multicomponent, mixed metal oxides (Bi3FeMo2O12, Bi2Mo2.5W0.5O12, and Bi1-x/3V1-xMoxO4, where 0 ≤ x ≤ 1) correlates with the band gap of the catalyst measured at reaction temperature. We show through theoretical analysis of the energy components comprising the activation energy why the band-gap energy is the primary component dependent on catalyst composition and, hence, why one should expect the activation energy for propene oxidation to correlate with the band-gap energy. We also demonstrate that the change in band-gap energy with composition arises from the interplay between the sizes and energies of the V 3d, Fe 3d, Mo 4d, and W 5d orbitals, which give rise to the lowest unoccupied crystal orbitals. Both the utility of the band-gap energy as a descriptor for catalytic activity and the role of orbital overlap in determining the band gap are likely to be general features in mixed metal oxide oxidation catalysts, enabling the rational design of catalysts with greater activity for oxidation reactions.

Prediction of solid oxide fuel cell cathode activity with first-principles descriptors

In this work we demonstrate that the experimentally measured area specific resistance and oxygen surface exchange of solid oxide fuel cell cathode perovskites are strongly correlated with the first-principles calculated oxygenp-band center and vacancy formation energy. These quantities are therefore descriptors of catalytic activity that can be used in the first-principles design of new SOFC cathodes.